A multi-criteria optimization and decision-making approach for improvement of food engineering processes.

The objective of this study was to propose a multi-criteria optimization and decision-making technique to solve food engineering problems. This technique was demostrated using experimental data obtained on osmotic dehydratation of carrot cubes in a sodium chloride solution. The Aggregating Functions Approach, the Adaptive Random Search Algorithm, and the Penalty Functions Approach were used in this study to compute the initial set of non-dominated or Pareto-optimal solutions. Multiple non-linear regression analysis was performed on a set of experimental data in order to obtain particular multi-objective functions (responses), namely water loss, solute gain, rehydration ratio, three different colour criteria of rehydrated product, and sensory evaluation (organoleptic quality). Two multi-criteria decision-making approaches, the Analytic Hierarchy Process (AHP) and the Tabular Method (TM), were used simultaneously to choose the best alternative among the set of non-dominated solutions. The multi-criteria optimization and decision-making technique proposed in this study can facilitate the assessment of criteria weights, giving rise to a fairer, more consistent, and adequate final compromised solution or food process. This technique can be useful to food scientists in research and education, as well as to engineers involved in the improvement of a variety of food engineering processes.

Global optimization of solar thermophotovoltaic systems

n this paper, we present a theoretical model based on the detailed balance theory of solar thermophotovoltaic systems comprising multijunction photovoltaic cells, a sunlight concentrator and spectrally selective surfaces. The full system has been defined by means of 2n + 8 variables (being n the number of sub-cells of the multijunction cell). These variables are as follows: the sunlight concentration factor, the absorber cut-off energy, the emitter-to-absorber area ratio, the emitter cut-off energy, the band-gap energy(ies) and voltage(s) of the sub-cells, the reflectivity of the cells' back-side reflector, the emitter-to-cell and cell-to-cell view factors and the emitter-to-cell area ratio. We have used this model for carrying out a multi-variable system optimization by means of a multidimensional direct-search algorithm. This analysis allows to find the set of system variables whose combined effects results in the maximum overall system efficiency. From this analysis, we have seen that multijunction cells are excellent candidates to enhance the system efficiency and the electrical power density. Particularly, multijunction cells report great benefits for systems with a notable presence of optical losses, which are unavoidable in practical systems. Also, we have seen that the use of spectrally selective absorbers, rather than black-body absorbers, allows to achieve higher system efficiencies for both lower concentration and lower emitter-to-absorber area ratio. Finally, we have seen that sun-to-electricity conversion efficiencies above 30% and electrical power densities above 50 W/cm2 are achievable for this kind of systems.

Mission profile based optimization of a wearable power system

A Wearable Power System (WPS) is a portable power source utilized primarily to power the modern soldier’s electronic equipment. Such a system has to satisfy output power demands in the range of 20 W...200 W, specified as a 4-day mission profile and has a weight limit of 4 kg. To meet these demands, an optimization of a WPS, comprising an internal combustion (IC) engine, permanent magnetic three-phase electrical motor/generator, inverter, Li-batteries, DC-DC converters, and controller, is performed in this paper. The mechanical energy extracted from the fuel by IC engine is transferred to the generator that is used to recharge the battery and provide the power to the electrical output load. The main objectives are to select the engine, fuel and battery type, to match the weight of fuel and the number of battery cells, to find the optimal working point of engine and to minimize the system weight. To provide the second output voltage level of 14 VDC, a separate DC-DC converter is connected between the battery and the load, and optimized for the specified mission profile. A prototype of the WPS based on the optimization presented in the paper results in a total system weight of 3.9 kg and fulfils the mission profile.

Design and Multi-Objective Optimization of EMI Input Filters

An EMI filter design procedure for power converters is proposed. Based on a given noise spectrum, information about the converter noise source impedance and design constraints, the design space of the input filter is defined. The design is based on component databases and detailed models of the filter components, including high frequency parasitics, losses, weight, volume, etc.. The design space is mapped onto a performance space in which different filter implementations are evaluated and compared. A multi-objective optimization approach is used to obtain optimal designs w.r.t. a given performance function.

Two design methods for radial line slot antennas with arbitrary or beam pattern

Two design procedures for Radial Line Slot Antennas (RLSAs) with circular polarization and either maximum gain or an arbitrary shaped pattern are proposed. Firstly, a method to design a RLSA with any desired pattern is presented. It is based on an optimization algorithm and some measures to ensure its fast convergence and stability need to be taken. Secondly, a fast technique to calculate the length and the position of every slot in a high gain RLSA with uniform field distribution is described. Both procedures are vali dated with the design of three antennas with different characteristics.

Multi-objective Aerodynamic Optimization of High-speed Trains in Tunnels

A genetic algorithm (GA) is employed for the multi-objective shape optimization of the nose of a high-speed train. Aerodynamic problems observed at high speeds become still more relevant when traveling along a tunnel. The objective is to minimize both the aerodynamic drag and the amplitude of the pressure gradient of the compression wave when a train enters a tunnel. The main drawback of GA is the large number of evaluations need in the optimization process. Metamodels-based optimization is considered to overcome such problem. As a result, an explicit relationship between pressure gradient and geometrical parameters is obtained.

Inestabilidad de pórticos planos metálicos de edificación con inclusión de la flexibilidad de las uniones y elementos no prismáticos : un enfoque para la optimización

En esta tesis se aborda el problema de la modelización, análisis y optimización de pórticos metálicos planos de edificación frente a los estados límites último y de servicio. El objetivo general es presentar una técnica secuencial ordenada de optimización discreta para obtener el coste mínimo de pórticos metálicos planos de edificación, teniendo en cuenta las especificaciones del EC-3, incorporando las uniones semirrígidas y elementos no prismáticos en el proceso de diseño. Asimismo se persigue valorar su grado de influencia sobre el diseño final. El horizonte es extraer conclusiones prácticas que puedan ser de utilidad y aplicación simple para el proyecto de estructuras metálicas. La cantidad de publicaciones técnicas y científicas sobre la respuesta estructural de entramados metálicos es inmensa; por ello se ha hecho un esfuerzo intenso en recopilar el estado actual del conocimiento, sobre las líneas y necesidades actuales de investigación. Se ha recabado información sobre los métodos modernos de cálculo y diseño, sobre los factores que influyen sobre la respuesta estructural, sobre técnicas de modelización y de optimización, al amparo de las indicaciones que algunas normativas actuales ofrecen sobre el tema. En esta tesis se ha desarrollado un procedimiento de modelización apoyado en el método de los elementos finitos implementado en el entorno MatLab; se han incluido aspectos claves tales como el comportamiento de segundo orden, la comprobación ante inestabilidad y la búsqueda del óptimo del coste de la estructura frente a estados límites, teniendo en cuenta las especificaciones del EC-3. También se ha modelizado la flexibilidad de las uniones y se ha analizado su influencia en la respuesta de la estructura y en el peso y coste final de la misma. Se han ejecutado algunos ejemplos de aplicación y se ha contrastado la validez del modelo con resultados de algunas estructuras ya analizadas en referencias técnicas conocidas. Se han extraído conclusiones sobre el proceso de modelización y de análisis, sobre la repercusión de la flexibilidad de las uniones en la respuesta de la estructura. El propósito es extraer conclusiones útiles para la etapa de proyecto. Una de las principales aportaciones del trabajo en su enfoque de optimización es la incorporación de una formulación de elementos no prismáticos con uniones semirrígidas en sus extremos. Se ha deducido una matriz de rigidez elástica para dichos elementos. Se ha comprobado su validez para abordar el análisis no lineal; para ello se han comparado los resultados con otros obtenidos tras aplicar otra matriz deducida analíticamente existente en la literatura y también mediante el software comercial SAP2000. Otra de las aportaciones de esta tesis es el desarrollo de un método de optimización del coste de pórticos metálicos planos de edificación en el que se tienen en cuenta aspectos tales como las imperfecciones, la posibilidad de incorporar elementos no prismáticos y la caracterización de las uniones semirrígidas, valorando la influencia de su flexibilidad sobre la respuesta de la estructura. Así, se han realizado estudios paramétricos para valorar la sensibilidad y estabilidad de las soluciones obtenidas, así como rangos de validez de las conclusiones obtenidas. This thesis deals with the problems of modelling, analysis and optimization of plane steel frames with regard to ultimate and serviceability limit states. The objective of this work is to present an organized sequential technique of discrete optimization for achieving the minimum cost of plane steel frames, taking into consideration the EC-3 specifications as well as including effects of the semi-rigid joints and non-prismatic elements in the design process. Likewise, an estimate of their influence on the final design is an aim of this work. The final objective is to draw practical conclusions which can be handful and easily applicable for a steel-structure project. An enormous amount of technical and scientific publications regarding steel frames is currently available, thus making the achievement of a comprehensive and updated knowledge a considerably hard task. In this work, a large variety of information has been gathered and classified, especially that related to current research lines and needs. Thus, the literature collected encompasses references related to state-of-the-art design methods, factors influencing the structural response, modelling and optimization techniques, as well as calculation and updated guidelines of some steel Design Codes about the subject. In this work a modelling procedure based on the finite element implemented within the MatLab programming environment has been performed. Several keys aspects have been included, such as second order behaviour, the safety assessment against structural instability and the search for an optimal cost considering the limit states according to EC-3 specifications. The flexibility of joints has been taken into account in the procedure hereby presented; its effects on the structural response, on the optimum weight and on the final cost have also been analysed. In order to confirm the validity and adequacy of this procedure, some application examples have been carried out. The results obtained were compared with those available from other authors. Several conclusions about the procedure that comprises modelling, analysis and design stages, as well as the effect of the flexibility of connections on the structural response have been drawn. The purpose is to point out some guidelines for the early stages of a project. One of the contributions of this thesis is an attempt for optimizing plane steel frames in which both non-prismatic beam-column-type elements and semi-rigid connections have been considered. Thus, an elastic stiffness matrix has been derived. Its validity has been tested through comparing its accuracy with other analytically-obtained matrices available in the literature, and with results obtained by the commercial software SAP2000. Another achievement of this work is the development of a method for cost optimization of plane steel building frames in which some relevant aspects have been taken in consideration. These encompass geometric imperfections, non-prismatic beam elements and the numerical characterization of semi-rigid connections, evaluating the effect of its flexibility on the structural response. Hence, some parametric analyses have been performed in order to assess the sensitivity, the stability of the outcomes and their range of applicability as well.

Spatial sampling methods for improved communication for wireless relay robots

Having reliable wireless communication in a network of mobile robots is an ongoing challenge, especially when the mobile robots are given tasks in hostile or harmful environments such as radiation environments in scientific facilities, tunnels with large metallic components and complicated geometries as found at CERN. In this paper, we propose a decentralised method for improving the wireless network throughput by optimizing the wireless relay robot position to receive the best wireless signal strength using implicit spatial diversity concepts and gradient-search algorithms. We experimentally demonstrate the effectiveness of the proposed solutions with a KUKA Youbot omni-directional mobile robot. The performance of the algorithms is compared under various scenarios in an underground scientific facility at CERN.

Laser Processes for Contact Optimization in c-Si Solar Cells

Solid State Lasers (SSL) have been used in microelectronic and photovoltaic (PV) industry for decades but, currently, laser technology appears as a key enabling technology to improve efficiency and to reduce production costs in high efficiency solar cells fabrication. Moreover, the fact that the interaction between the laser radiation and the device is normally localized and restricted to a controlled volume makes SSL a tool of choice for the implementation of low temperature concepts in PV industry. Specifically, SSL are ideally suited to improve the electrical performance of the contacts further improving the efficiency of these devices. Advanced concepts based on standard laser firing or advanced laser doping techniques are optimal solutions for the back contact of a significant number of structures of growing interest in the c-Si PV industry, and a number of solutions has been proposed as well for emitter formation, to reduce the metallization optical losses or even to remove completely the contacts from the front part of the cell. In this work we present our more recent results of SSL applications for contact optimization in c-Si solar cell technology, including applications on low temperature processes demanding devices, like heterojunction solar cells.

Automatic design of Ant Colony Optimization for permutation problems

In this study, we present a framework based on ant colony optimization (ACO) for tackling combinatorial problems. ACO algorithms have been applied to many diferent problems, focusing on algorithmic variants that obtain high-quality solutions. Usually, the implementations are re-done for various problem even if they maintain the same details of the ACO algorithm. However, our goal is to generate a sustainable framework for applications on permutation problems. We concentrate on understanding the behavior of pheromone trails and specific methods that can be combined. Eventually, we will propose an automatic offline configuration tool to build an efective algorithm. ---RESUMEN---En este trabajo vamos a presentar un framework basado en la familia de algoritmos ant colony optimization (ACO), los cuales están dise~nados para enfrentarse a problemas combinacionales. Los algoritmos ACO han sido aplicados a diversos problemas, centrándose los investigadores en diversas variantes que obtienen buenas soluciones. Normalmente, las implementaciones se tienen que rehacer, inclusos si se mantienen los mismos detalles para los algoritmos ACO. Sin embargo, nuestro objetivo es generar un framework sostenible para aplicaciones sobre problemas de permutaciones. Nos centraremos en comprender el comportamiento de la sendas de feromonas y ciertos métodos con los que pueden ser combinados. Finalmente, propondremos una herramienta para la configuraron automática offline para construir algoritmos eficientes.

Two-dimensional mesh optimization in the finite element method

The solution to the problem of finding the optimum mesh design in the finite element method with the restriction of a given number of degrees of freedom, is an interesting problem, particularly in the applications method. At present, the usual procedures introduce new degrees of freedom (remeshing) in a given mesh in order to obtain a more adequate one, from the point of view of the calculation results (errors uniformity). However, from the solution of the optimum mesh problem with a specific number of degrees of freedom some useful recommendations and criteria for the mesh construction may be drawn. For 1-D problems, namely for the simple truss and beam elements, analytical solutions have been found and they are given in this paper. For the more complex 2-D problems (plane stress and plane strain) numerical methods to obtain the optimum mesh, based on optimization procedures have to be used. The objective function, used in the minimization process, has been the total potential energy. Some examples are presented. Finally some conclusions and hints about the possible new developments of these techniques are also given.

Efficient Monte Carlo optimization for multi-label classifier chains

Multi-label classification (MLC) is the supervised learning problem where an instance may be associated with multiple labels. Modeling dependencies between labels allows MLC methods to improve their performance at the expense of an increased computational cost. In this paper we focus on the classifier chains (CC) approach for modeling dependencies. On the one hand, the original CC algorithm makes a greedy approximation, and is fast but tends to propagate errors down the chain. On the other hand, a recent Bayes-optimal method improves the performance, but is computationally intractable in practice. Here we present a novel double-Monte Carlo scheme (M2CC), both for finding a good chain sequence and performing efficient inference. The M2CC algorithm remains tractable for high-dimensional data sets and obtains the best overall accuracy, as shown on several real data sets with input dimension as high as 1449 and up to 103 labels.

A Multi Ant Colony Optimization algorithm for a Mixed Car Assembly Line

This paper presents an ant colony optimization algorithm to sequence the mixed assembly lines considering the inventory and the replenishment of components. This is a NP-problem that cannot be solved to optimality by exact methods when the size of the problem growth. Groups of specialized ants are implemented to solve the different parts of the problem. This is intended to differentiate each part of the problem. Different types of pheromone structures are created to identify good car sequences, and good routes for the replenishment of components vehicle. The contribution of this paper is the collaborative approach of the ACO for the mixed assembly line and the replenishment of components and the jointly solution of the problem.

Energy Management and Optimization for Video Decoders based on Functional-oriented Reconfiguration

In recent years, the increasing sophistication of embedded multimedia systems and wireless communication technologies has promoted a widespread utilization of video streaming applications. It has been reported in 2013 that youngsters, aged between 13 and 24, spend around 16.7 hours a week watching online video through social media, business websites, and video streaming sites. Video applications have already been blended into people daily life. Traditionally, video streaming research has focused on performance improvement, namely throughput increase and response time reduction. However, most mobile devices are battery-powered, a technology that grows at a much slower pace than either multimedia or hardware developments. Since battery developments cannot satisfy expanding power demand of mobile devices, research interests on video applications technology has attracted more attention to achieve energy-efficient designs. How to efficiently use the limited battery energy budget becomes a major research challenge. In addition, next generation video standards impel to diversification and personalization. Therefore, it is desirable to have mechanisms to implement energy optimizations with greater flexibility and scalability. In this context, the main goal of this dissertation is to find an energy management and optimization mechanism to reduce the energy consumption of video decoders based on the idea of functional-oriented reconfiguration. System battery life is prolonged as the result of a trade-off between energy consumption and video quality. Functional-oriented reconfiguration takes advantage of the similarities among standards to build video decoders reconnecting existing functional units. If a feedback channel from the decoder to the encoder is available, the former can signal the latter changes in either the encoding parameters or the encoding algorithms for energy-saving adaption. The proposed energy optimization and management mechanism is carried out at the decoder end. This mechanism consists of an energy-aware manager, implemented as an additional block of the reconfiguration engine, an energy estimator, integrated into the decoder, and, if available, a feedback channel connected to the encoder end. The energy-aware manager checks the battery level, selects the new decoder description and signals to build a new decoder to the reconfiguration engine. It is worth noting that the analysis of the energy consumption is fundamental for the success of the energy management and optimization mechanism. In this thesis, an energy estimation method driven by platform event monitoring is proposed. In addition, an event filter is suggested to automate the selection of the most appropriate events that affect the energy consumption. At last, a detailed study on the influence of the training data on the model accuracy is presented. The modeling methodology of the energy estimator has been evaluated on different underlying platforms, single-core and multi-core, with different characteristics of workload. All the results show a good accuracy and low on-line computation overhead. The required modifications on the reconfiguration engine to implement the energy-aware manager have been assessed under different scenarios. The results indicate a possibility to lengthen the battery lifetime of the system in two different use-cases.

Desing and development of a robotic platform for the evaluation of search algorithms

Plant diseases represent a major economic and environmental problem in agriculture and forestry. Upon infection, a plant develops symptoms that affect different parts of the plant causing a significant agronomic impact. As many such diseases spread in time over the whole crop, a system for early disease detection can aid to mitigate the losses produced by the plant diseases and can further prevent their spread [1]. In recent years, several mathematical algorithms of search have been proposed [2,3] that could be used as a non-invasive, fast, reliable and cost-effective methods to localize in space infectious focus by detecting changes in the profile of volatile organic compounds. Tracking scents and locating odor sources is a major challenge in robotics, on one hand because odour plumes consists of non-uniform intermittent odour patches dispersed by the wind and on the other hand because of the lack of precise and reliable odour sensors. Notwithstanding, we have develop a simple robotic platform to study the robustness and effectiveness of different search algorithms [4], with respect to specific problems to be found in their further application in agriculture, namely errors committed in the motion and sensing and to the existence of spatial constraints due to land topology or the presence of obstacles.